Right now, there are 1,851 emojis supported by the Unicode Consortium, including everything from a purple eggplant to a ghost with its tongue sticking out. That's roughly 10 times as many symbols as you can type on an English QWERTY keyboard, and that number's only growing.

But despite the runaway popularity of these curious cartoon symbols, the way we actually type out emojis is very primitive: a tiny separate keyboard on our smartphones, roughly organized by category, that even the best emoji users haven't so much mastered as partially memorized. "Emoji has a big UI problem," says Xavier Snelgrove. It's a problem that his company, Whirlscape, is trying to solve with artificial intelligence. The company has created an Android app called Dango that uses recurring neural networks to automatically predict what emojis you want to use based on your message.

On Android, Dango exists as a virtual on-screen helper—like Clippy for Emoji. A pink cube resembling an anthropomorphic cube of Turkish Delight, Dango suggests emojis as you type in a word balloon, which can then be placed in your message just by tapping on them. It works in any app, and even any keyboard, at least on Android. (When the iOS version of Dango ships later this year, it will need to exist as its own keyboard app, because of Apple's more stringent developer policies.)

But more impressive than how it appears on-screen is what Dango's doing behind the scenes. Snelgrove says that over the last two years, Whirlscape has been training a neural network on a massive archive of scraped Twitter and Instagram data to "understand" the language of emojis, as it is used online. And that language is a lot less obvious than it might at first appear.

Type Kanye, and Dango will suggest a flame emoji, because Kanye's latest track is on fire. Or the praising hands, because all hail Yeezus.

Although every emoji technically has a description attached to it, these descriptions don't always correspond to the way they're used in the real world. A purple eggplant, for example, is usually used as emoji shorthand for a penis—not a polite dinner suggestion. This is a distinction, though, that Dango well understands, as well as high-quality emoji suggestions such as a kitty face or a peach for other unmentionables. Mention drugs, meanwhile, and Dango will suggest the plug emoji, a slang emoji for a big-time dealer.

Nor is Dango's emoji savviness limited to the profane or criminal. Type Kanye, and Dango will suggest a flame emoji, because Kanye's latest track is on fire. It will then suggest a goat, because Kanye fans use this as shorthand for him being the greatest of all time: G.O.A.T. Next, a pair of earbuds with musical notes coming out of them, the meaning of which is obvious. And finally, the praising hands, because all hail Yeezus. Dango treats mentions of Beyoncé the same way, suggesting a crown and a bumblebee for the Queen B.

Dango is so good at emojis, it can make even a clueless 37-year-old like me seem as "with it" as any millennial Snapchatter when he's texting, provided he resists the urge to type "with it" in quotes.

It's this ability of AI to enrich the ways in which we communicate, and even bridge cultural or linguistic divides, which really excites Snelgrove. Today, an AI like Dango might only help us communicate with each other in emojis. But in the future, it could work as a slang translator, a writing coach, or even an in-app Cyrano de Bergerac helping you craft the perfect Tinder profile. "It's absurd," says Snelgrove, to think that the future of messaging will ever just be chatbots messaging chatbots, because people will always want and need to talk to one another. But that doesn't mean we won't ask neural networks like Dango to be our wingmen. Or, rather, our wingbots.